Production-aware AI copilot for Apache Spark
DataFlint reads your Spark logs and plans, pinpoints bottlenecks, and proposes IDE fixes. Monitors jobs and surfaces optimization opportunities and cost savings so teams ship faster with 10× the impact.
IDE Extension - AI Copilot
Production-aware suggestions in your editor based on real Spark runs. Highlight performance issues and get one-click fixes with expected impact.
Job Debugger & Optimizer
Modern Spark Web UI tab that makes plans and stages readable, flags bottlenecks, and helps you fix failing or slow jobs in minutes.
DataFlint Dashboard
Company-wide observability and cost optimization. See every Spark job, quantify spend, and fix the right things first with $ impact ranking.
Complete Spark Optimization Workflow
From production monitoring to IDE fixes - close the loop on Spark optimization
1. Monitor
Dashboard surfaces performance issues and cost optimization opportunities
2. Debug
Web UI tab helps you understand what's happening and why jobs are slow
3. Fix
IDE extension provides AI-powered suggestions with one-click fixes
From Hours of Guesswork to Minutes of Precision
Most teams spend hours debugging Spark jobs with basic tools. DataFlint transforms this into a systematic, data-driven workflow.
Current State (Manual process)
- •4-8 hours to root cause issues manually
- •Guesswork to identify bottlenecks
- •Manual code fixes with context switching
- •No visibility into costs or optimization impact
DataFlint (AI-powered solution)
- •2-5 minutes with AI-powered analysis
- •Auto-detection with impact ranking
- •IDE integration with one-click fixes
- •Stage/team cost attribution with $ optimization ranking